Healthcare Chatbots: Role of AI, Benefits, Future, Use Cases, Development

Artificial intelligence (AI) systems capable of conducting and interpreting such dialogues could enhance medical accessibility and improve quality. Although the use of NLP is a new territory in the health domain [47], it is a well-studied area in computer science and HCI. The majority (28/32, 88%) of the studies contained very little description of the technical implementation of the chatbot, which made it difficult to classify the chatbots from this perspective.

However, healthcare data is often stored in disparate systems that are not integrated. Healthcare providers can overcome this challenge by investing in data integration technologies that allow chatbots to access patient data in real-time. A well built healthcare chatbot with natural language processing (NLP) can understand user intent with the help of sentiment analysis. Based on the understanding of the user input, the bot can recommend appropriate healthcare plans.

Chatbot is Available 24/7

The remaining inaccuracies could be detrimental to the patient’s health, receiving false information about their potential condition. This story is part of a series on the current progression in Regenerative Medicine. The data can be saved further making patient admission, symptom tracking, doctor-patient contact, and medical record-keeping easier. And while these tools’ rise in popularity can be accredited to the very nature of the COVID-19 pandemic, AI’s role in healthcare has been growing steadily on its own for years — and that’s anticipated to continue. When the request is understood, action execution and information retrieval take place. The chatbot performs the requested actions or retrieves the data of interest from its data sources, which may be a database, known as the Knowledge Base of the chatbot, or external resources that are accessed through an API call [35].

Inarguably, this is one of the critical factors that influence customer satisfaction and a company’s brand image (including healthcare organizations, naturally). With standalone chatbots, businesses have been able to drive their customer support experiences, but it has been marred with flaws, quite expectedly. You do not design a conversational pathway the way you perceive your intended users, but with real customer data that shows how they want their conversations to be. Hopefully, after reviewing these samples of the best healthcare chatbots above, you’ll be inspired by how your chatbot solution for the healthcare industry can enhance provider/patient experiences. To develop a chatbot that engages and provides solutions to users, chatbot developers need to determine what types of chatbots in healthcare would most effectively achieve these goals.

Chatbot Ensures Quick Access To Vital Details

Accredited physicians must remain the primary decision-makers in a patient’s medical journey. Dr. Rachel Goodman and colleagues at Vanderbilt University investigated chatbox responses in a recent study in Jama. Their study tested ChatGPT-3.5 and the updated GPT-4 using 284 physician-prompted questions to determine accuracy, completeness, and consistency over time.

This requires the same kind of plasticity from conversations as that between human beings. The division of task-oriented and social chatbots requires additional elements to show the relation among users, experts (professionals) and chatbots. Most chatbot cases—at least task-oriented chatbots—seem to be user facing, that is, they are like a ‘gateway’ between the patient and the HCP. In the case of Omaolo, for example, it seems that it was used extensively for diagnosing conditions that were generally considered intimate, such as urinary tract infections and sexually transmitted diseases (STDs) (Pynnönen et al. 2020, p. 24). This relieving of pressure on contact centres is especially important in the present COVID-19 situation (Dennis et al. 2020, p. 1727), thus making chatbots cost-effective. However, one of the key elements for bots to be trustworthy—that is, the ability to function effectively with a patient—‘is that people believe that they have expertise’ (Nordheim et al. 2019).

Faster processing of queries

Health Hero (Health Hero, Inc), Tasteful Bot (Facebook, Inc), Forksy (Facebook, Inc), and SLOWbot (iaso heath, Inc) guide users to make informed decisions on food choices to change unhealthy eating habits [48,49]. The effectiveness of these apps cannot be concluded, as a more rigorous analysis of the development, evaluation, and implementation is required. Nevertheless, chatbots are emerging as a solution chatbot technology in healthcare for healthy lifestyle promotion through access and human-like communication while maintaining anonymity. In terms of cancer diagnostics, AI-based computer vision is a function often used in chatbots that can recognize subtle patterns from images. This would increase physicians’ confidence when identifying cancer types, as even highly trained individuals may not always agree on the diagnosis [52].

QliqSOFT’s Quincy chatbot solution, which is powered by an AI engine and driven by natural-language processing, enables real-time, patient-centered collaboration through text messaging. The tool helps patients with everything from finding a doctor and scheduling appointments to outpatient monitoring and much more. We consider that this research provides useful information about the basic principles of chatbots. Users and developers can have a more precise understanding of chatbots and get the ability to use and create them appropriately for the purpose they aim to operate. Understanding what the chatbot will offer and what category falls into helps developers pick the algorithms or platforms and tools to build it. RiveScript is a plain text, line-based scripting language for the development of chatbots and other conversational entities.

2 ADA HEALTH

The challenge here for software developers is to keep training chatbots on COVID-19-related verified updates and research data. As researchers uncover new symptom patterns, these details need to be integrated into the ML training data to enable a bot to make an accurate assessment of a user’s symptoms at any given time. Recently the World Health Organization (WHO) partnered with Ratuken Viber, a messaging app, to develop an interactive chatbot that can provide accurate information about COVID-19 in multiple languages. With this conversational AI, WHO can reach up to 1 billion people across the globe in their native languages via mobile devices at any time of the day.